Multivector-based model predictive direct speed control (MV-MPDSC) suffers from outer loop disturbance, inner loop disturbance, and weighting factor tuning. To solve these problems, a multivector-based model-free predictive speed control (MV-MFPSC) is proposed for the surface-mounted permanent magnet synchronous motors (SPMSMs). First, a reduced-order ultralocal model is established by introducing an equivalent speed-tracking error as a state variable, which derives the outer and inner loop disturbances as a lumped disturbance while compensating for differences between mechanical and electromagnetic time constants. It reduces the number of observers and the speed overshoot/oscillation. Theoretical analysis indicates that the nonlinear extended state observer (NESO) exhibits a poor estimation performance facing the lumping disturbance of large-scale changes. Thus, a modified NESO (MNESO) is introduced to achieve a faster and more accurate lumped disturbance estimation, which significantly improves the dynamic performance. Moreover, its parameter design principles are proposed to enhance the practicality. Then, an algebraic minimizing approach is introduced to directly calculate the duty cycle of the selected voltage vectors, and the weighting factors can be eliminated through clever mathematical operation. It avoids the duty cycle calculation error caused by imperfect weighting factors and improves the steady-state performance. The effectiveness of the MV-MFPSC was demonstrated through experiments.


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    Title :

    Multivector-Based Model-Free Predictive Speed Control With Disturbance Suppression and Weighting Factor Elimination for SPMSM


    Contributors:
    Yang, Meizhou (author) / Wang, Pengda (author) / Huang, Sheng (author) / Liao, Wu (author) / Wu, Xuan (author) / Liang, Ge (author) / Wu, Ting (author) / Liu, Xicai (author) / Li, Xing (author) / Huang, Shoudao (author)


    Publication date :

    2025-02-01


    Size :

    4012082 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English